The system is called LatentGesture and was used during a Georgia Tech lab study using Android devices. The system was nearly 98 percent accurate on a smartphone and 97 percent correct on tablets. The research team will present the findings for the first time at the end of April.
"The system learns a person's 'touch signature,' then constantly compares it to how the current user is interacting with the device," said Polo Chau, a Georgia Tech College of Computing assistant professor who led the study.
To test the system, Chau and his team set up an electronic form with a list of tasks for 20 participants. They were asked to tap buttons, check boxes and swipe slider bars on a phone and tablet to fill out the form. The system tracked their tendencies and created a profile for each person.
After profiles were stored, the researchers designated one person's signature as the "owner" of the device and repeated the tests. LatentGesture successfully matched the owner and flagged everyone else as unauthorized users.
"Just like your fingerprint, everyone is unique when they use a touchscreen," said Chau. "Some people slide the bar with one quick swipe. Others gradually move it across the screen. Everyone taps the screen with different pressures while checking boxes."
The research team also programmed the system to store five touch signatures on the same device – one "owner" and four authorized users. When someone other than the owner used the tablet, the system identified each with 98 percent accuracy.